python - count rows by certain combination of row values pandas

Question

I have a dataframe (df) like this:

  v1    v2  v3
   0    -30 -15
   0    -30 -7.5
   0    -30 -11.25
   0    -30 -13.125
   0    -30 -14.0625
   0    -30 -13.59375
   0    -10 -5
   0    -10 -7.5
   0    -10 -6.25
   0    -10 -5.625
   0    -10 -5.9375
   0    -10 -6.09375
   0    -5  -2.5
   0    -5  -1.25
   0    -5  -1.875

The rows are in the same chunk if with certain/same v1 and v2. In this case, rows with([0,-30], [0,-10], [0,-5]). I want to split the rows in chunks and count the number of rows in this chunk. If the length of the rows is not 6, then remove the whole chunk, otherwise, keep this chunk.

My rough codes:

v1_ls = df.v1.unique()
v2_ls = df.v2.unique()
for i, j in v1_ls, v2_ls: 
   chunk[i] = df[(df['v1'] == v1_ls[i]) & df['v2'] == v2_ls[j]]

   if len(chunk[i])!= 6:
      df = df[df != chunk[i]]
   else:
      pass

expected output:

  v1    v2  v3
   0    -30 -15
   0    -30 -7.5
   0    -30 -11.25
   0    -30 -13.125
   0    -30 -14.0625
   0    -30 -13.59375
   0    -10 -5
   0    -10 -7.5
   0    -10 -6.25
   0    -10 -5.625
   0    -10 -5.9375
   0    -10 -6.09375

Thanks!

Answer 1

You can use the filter groupby method:

In [11]: df.groupby(['v1', 'v2']).filter(lambda x: len(x) == 6)
Out[11]:
    v1  v2        v3
0    0 -30 -15.00000
1    0 -30  -7.50000
2    0 -30 -11.25000
3    0 -30 -13.12500
4    0 -30 -14.06250
5    0 -30 -13.59375
6    0 -10  -5.00000
7    0 -10  -7.50000
8    0 -10  -6.25000
9    0 -10  -5.62500
10   0 -10  -5.93750
11   0 -10  -6.09375